A Common Vision for Undergraduate Mathematical Sciences Programs in 2025 FINAL DRAFT. Karen Saxe Linda Braddy

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A Common Vision for

Undergraduate Mathematical Sciences Programs

in 2025

FINAL DRAFT

Karen Saxe

Linda Braddy

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About the project

The Common Vision project is a joint effort, focused on modernizing undergraduate programs in the mathematical sciences, of the American Mathematical Association of Two-Year Colleges (AMATYC), the American Mathematical Society (AMS), the American Statistical Association (ASA), the Mathematical Association of America (MAA), and the Society of Industrial and Applied Mathematics (SIAM).

Acknowledgements

Thanks to funding from the National Science Foundation (NSF DUE-1446000), we were able to bring together individuals with extensive experience related to undergraduate curricula in the math-ematical sciences to offer guidance on this project.

This report represents the collective wisdom of many individuals, and we would like to express our gratitude to all who participated. We do not view the distinct efforts of various associations as competing efforts, but instead as the basis and strong foundation for collective action that is well-informed by a variety of perspectives.

We are grateful to ASA and MAA staff for their critical support on everything from setting up the Common Visionwebsite to handling the logistics of the May 2015 workshop.

Leadership Team Members

Karen Saxe, Macalester College

Linda Braddy, Mathematical Association of America John Bailer, Miami University

Rob Farinelli, College of Southern Maryland Tara Holm, Cornell University

Vilma Mesa, University of Michigan Uri Treisman, University of Texas Peter Turner, Clarkson University

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Executive Summary

The Common Vision project brought together leaders from five professional associations – the American Mathematical Association of Two-Year Colleges (AMATYC), the American Mathemat-ical Society (AMS), the American StatistMathemat-ical Association (ASA), the MathematMathemat-ical Association of America (MAA), and the Society of Industrial and Applied Mathematics (SIAM) – to collectively reconsider undergraduate curricula and ways to improve education in the mathematical sciences. Project participants represented not only these mathematical sciences associations, but also partner STEM disciplines, higher education advocacy organizations, and industry.

We began with an in-depth examination of seven curricular guides published by these five associa-tions and spent a substantial amount of time identifying common themes in the guides. This report reflects a synthesis of these themes with our own research and input from project participants and other thought leaders in our community.

One of the most striking findings is that all seven guides emphasized this point, in particular:

The status quo is unacceptable.

Consequently, this report focuses on specific areas that require significant further action from the mathematical sciences community to improve undergraduate learning, especially in courses typically taken in the first two years. These areas fall into one of four categories: curricula, course structure, workforce preparation, and faculty development.

In this report, we call on the community to (1) update curricula, (2) articulate clear pathways between curricula driven by changes at the K-12 level and the first courses students take in col-lege, (3) scale up the use of evidence-based pedagogical methods, (4) find ways to remove barriers facing students at critical transition points (e.g., placement, transfer) and (5) establish stronger connections with other disciplines. Institutions should provide faculty with training, resources, and rewards for their efforts to adapt curricula, develop new courses, and incorporate pedagogical tools and technology to enhance student learning. Departments should update curricula, establish mul-tiple pathways into and through majors, and move toward environments that incorporate mulmul-tiple pedagogical approaches throughout a program. Instructors should present key ideas and concepts from a variety of perspectives, employ a broad range of examples and applications to motivate and illustrate the material, promote awareness of connections to other subjects, and introduce con-temporary topics and applications. Students should learn to communicate complex ideas in ways understandable to collaborators, clients, employers and other audiences.

To ensure students graduate with skill sets to match expectations of prospective employers, our community must modernize curricula with input from representatives in partner disciplines, busi-ness, industry, and government. This work should aim to narrow the gap between mathematics as practiced in the academy and other employment sectors and mathematics as experienced in higher education’s instructional programs. While intellectual domains fragment and coalesce over time, a central task for mathematics faculty at institutions of higher education, and more broadly, the mathematical sciences community as a whole, is to create a coherent, intriguing introduction to collegiate mathematics for all students.

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Moving forward, we believe it is critical to maintain the collective connection and dialogue among the associations established during this initial phase of Common Vision. This phase sought to effect changes in undergraduate mathematical sciences education in order to expand scientific knowledge and maintain a viable workforce in the United States. By reaching out to members of the five associations, we hoped to galvanize the mathematical sciences community and spur grassroots efforts to improve undergraduate education. Change is unquestionably coming to lower-division mathematics and statistics, and it is incumbent on the mathematical sciences community to ensure it is at the center of these changes, not on the periphery. We hope other individuals and groups will come alongside us in this effort, capitalize on the momentum we have built and goodwill we have established, and move this effort forward into a second phase focused on implementation initiatives.

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1 Introduction

Freshman and sophomore mathematics and statistics courses function as gateways to many majors, and they are crucial for preparing mathematically- and scientifically-literate citizens. Yet:

• Each year only about 50 percent of students earn a grade of A, B, or C in college algebra (Ganter & Haver, 2011).

• Women are almost twice as likely as men to choose not to continue beyond Calculus I, even when Calculus II is a requirement for their intended major (Bressoud, 2011).

• In 2012, 19.9 percent of all bachelor’s degrees were awarded to underrepresented minority students (9.5 percent to Blacks, 9.8 percent to Hispanics). However, only 11.6 percent of mathematics bachelor’s degrees were awarded to underrepresented minority students (4.9 percent to Blacks, 6.4 percent to Hispanics) (www.nsf.gov/statistics/nsf07308/content. cfm?pub_id=3633&id=2).

• Failure rates under traditional lecture are 55 percent higher than the rates observed under more active approaches to instruction (Freeman et al., 2014).

Additional challenges are outlined in reports such asThe Mathematical Sciences in 2025(National Research Council (NRC), 2013) and Engage to Excel: Producing One Million Additional College Graduates with Degrees in Science, Technology, Engineering, and Mathematics(President’s Council of Advisors on Science and Technology (PCAST), 2012). These reports have led to varied responses from subgroups within the mathematical sciences, including the launch of this Common Vision project. It is time for collective action to coordinate existing and future efforts in such a way that the mathematical sciences community is pulling in the same general direction and leveraging the collective power of the whole to improve student success, especially in the first two years of college. This project is intended as a new beginning, marking a period of increased interaction and collaboration among all stakeholders to improve post-secondary education in the mathematical sciences.

Over the past several decades, members of various mathematical sciences professional associations have devoted much thought to educational issues and published distinct curricular guides. This Common Visionreport integrates them into a single set of recommendations and provides a snapshot of the current collective thinking about undergraduate education in mathematics and statistics. It lays a foundation for future work that acknowledges the changing face of the mathematical sciences, particularly with respect to the inclusion of data science, modeling, and computation.

Undergraduate courses in the mathematical sciences that students take during the first two years range from developmental courses to regression analysis and differential equations; our focus is the collection of credit-bearing courses (i.e., “non-developmental”) in the mathematical sciences typically taken in the first two years. In this report, we examine the undergraduate program, including statistics, modeling, and computational mathematics as well as applications in the broader mathematically-based sciences using a wide-angle lens. We include actuarial studies and operations research, engineering and the physical sciences, the life and social sciences, and quantitative business topics like accounting. We examine the issue of multiple “pathways” in a variety of contexts, with

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our use of this term intended to encompass (1) pathways into majors in the mathematical sciences, (2) pathways through these majors, and (3) pathways through general education mathematics and statistics requirements. We include developmental curricula only when it cannot be divorced from general education issues. We recognize the importance of K-12 and developmental curricula in the full elementary-through-baccalaureate spectrum, but including recommendations such as those from the National Council of Teachers of Mathematics (NCTM) is beyond the scope of this project. The Common Vision project brought together leaders from five professional associations – the American Mathematical Association of Two-Year Colleges (AMATYC), the American Mathemat-ical Society (AMS), the American StatistMathemat-ical Association (ASA), the MathematMathemat-ical Association of America (MAA), and the Society of Industrial and Applied Mathematics (SIAM) – to collectively reconsider undergraduate mathematics curricula and ways to improve education in the mathemati-cal sciences at a two-and-a-half day workshop in May 2015 at ASA headquarters in the Washington, D.C., area. Workshop attendees represented not only the five aforementioned mathematical sci-ences associations, but also partner STEM disciplines, higher education advocacy organizations, and industries.

In this major cooperative effort to improve teaching and learning, we joined forces to address a wide range of issues affecting the critical first two years of collegiate mathematics and statistics. Common Visionis grounded in an in-depth examination of seven curricular guides published by the five professional associations involved in this project. We spent substantial time identifying common themes in these guides and determining areas for future work to improve undergraduate learning in the mathematical sciences, especially in courses typically taken in the first two years. One of the most striking findings is that all seven guides emphasized this point, in particular:

The status quo is unacceptable.

Essential to bringing about lasting change is a continuation of this collective Common Vision effort. We do not suggest a single prescription for all contexts but, rather, that work be done in counterpoint to create a tapestry of ideas.

We envision this project as Phase I of a two-part initiative. Phase I focuses on introspection: we seek internal coherence of vision within the mathematical sciences community. Phase II of the project will be an outward-looking period focused on widespread dissemination and large-scale implementation of modernized curricula and delivery methods. We are aiming to narrow the gap between today’s mathematics as it is practiced in the academy, industry, and government and how it is experienced in higher education’s instructional programs. Part of this modernization is recognizing the essential nature and breadth of mathematics as manifested in its extraordinary power to advance other fields and to find within these fields new problems worthy of mathematicians’ scrutiny. While intellectual domains fragment and coalesce over time, we believe that a central task for mathematics faculty at institutions of higher education, and more broadly, the mathematical sciences community as a whole, is to create a coherent, intriguing introduction to collegiate mathematics for all students. As we move forward, it is critical that we maintain the collective connection and dialogue among the associations we have established during this initial phase. We must also build on work done at higher education institutions that merits emulation and further study.

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There is a great deal of follow-up work to be done investigating the efficacy of existing recommen-dations related to undergraduate curricula and instructional methodologies. Evidence of effective programs exists, and many recommendations deserve additional consideration. Which recommen-dations have been implemented, and which have resulted in improved student outcomes? This project builds on past and current work as a way to avoid repeating our mistakes, re-inventing suc-cessful initiatives, and pursuing misguided directions. A central goal of the project is to motivate efforts to modernize programs in the mathematical sciences and produce an adequate number of graduates with strong mathematical competencies for the United States workforce. We examine past work and identify promising practices in curricula revision for the purpose of making exem-plary curricular and pedagogical initiatives visible to the broader community as the impetus for widespread implementation of modernized courses. This report can also guide funding agencies regarding best bets for targeted federal investments likely to have transformative impact within the community.

As practitioners in the mathematical sciences, we celebrate the beauty and power of mathematics. Courses in the mathematical sciences have been taught as part of a classical education for thousands of years and continue to gain new meaning and relevance. There are now, perhaps more than ever, amazing career opportunities for people with training in mathematically-intensive fields. Rapid advances in technology and in connections between mathematics and other fields present tremendous opportunities, and the mathematical sciences community is at a pivotal point. Politicians across the country and mathematical scientists, not just mathematics educators, are more keenly focused on undergraduate mathematics and statistics education issues than in the past. We are attempting to capitalize on the current climate to (1) advance our goal of a shared vision for modernized curricula and pedagogies and (2) improve the public perception of our field.

The mathematical sciences are in the national spotlight in part because mathematical competencies can lead to higher paying jobs, and thus can play a profound role in students’ economic mobility. There is substantial support for reforming undergraduate instruction in the mathematical sciences from influential actors: the White House Office of Science and Technology Policy, the National Academies, and the Association of American Universities, among others. We have taken advantage of this increased attention at the national level by writing a white paper for Dr. John Holdren, who is Assistant to the President for Science and Technology, Director of the White House Office of Science and Technology Policy, and co-chair of PCAST. We sent the paper to several Congressional members as well, including chairs and ranking members of the House and Senate committees on education. We also wrote calls-to-action to members of the mathematical sciences community and opinion pieces aiming to raise the visibility of this project, e.g., in an AMS blog (Saxe, 2015, May) and in the Association for Women in Mathematics Newsletter (Saxe, 2015, July-August). In our view, public perception will change more rapidly if the mathematical sciences community speaks with a unified voice; to this end, we are very pleased that Conference Board of the Mathematical Sciences (CBMS) has endorsed theCommon Visionproject as part of the constructive response to reports critical of our community (NRC, 2013; PCAST, 2012). All these communiqu´es are available at theCommon Visionwebsite (www.maa.org/common-vision).

This report is organized as follows:

In Chapter 1, we include background for this project, a brief description of the NRC (2013) and PCAST (2012) reports, and profiles of the five professional associations.

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In Chapter 2, we enumerate the common themes identified in the seven curricular guides.

In Chapter 3, we describe “next step” proposals developed by Common Vision participants for initiatives to advance this work.

1.1 Background

Our premises are:

• Mathematical scientists – including theoretical and applied mathematicians, statisticians, com-putational scientists, and mathematical sciences education researchers – contribute in fundamental ways to initiatives to advance national priorities in the interests of all citizens.

• The most productive approach to preparing the next generation of citizens literate in science, technology, engineering, and mathematics (STEM) will involve multidisciplinary teams of math-ematical scientists, other domain specialists from STEM and non-STEM fields, and employers working together to modernize undergraduate mathematics and statistics programs.

• Mathematical sciences courses in the first two years of college function as pathways into many different STEM majors and also as key components in the preparation of scientifically-literate citizens.

Society benefits from college graduates who are generally educated in higher mathemat-ics, whose lives and social activities are influenced by their understanding of mathe-matics and, through it, of interesting aspects of history and culture. Beyond career and employment issues, “pure” mathematics majors are parents, aunts, uncles, volunteers in schools, tutors, voters in elections, school board members. Pure mathematics courses, including those driven mainly by aesthetic concerns, can help prepare students to be-come valuable citizens, all of whose contributions are augmented by skills and habits of mind developed through learning mathematics (MAA, 2015, p. 61).

Specific ways in which knowledge in the mathematical sciences can contribute to societal problems are outlined in, for example, The Future Postponed, a report by the MIT Committee to Evaluate the Innovation Deficit (MIT, 2015).

1.2 Impetus to change

We initiated this project in response to national calls to improve undergraduate education in the mathematical sciences. These calls include, but are not limited to: Engage to Excel: Producing One Million Additional College Graduates with Degrees in Science, Technology, Engineering, and Mathematics (PCAST, 2012) and The Mathematical Sciences in 2025 (NRC, 2013). These two reports in particular criticized the collective enterprise of teaching mathematics to undergraduates. We are also responding to the fact that the higher education environment has undergone and continues to experience significant changes. Changes are particularly profound in the areas of:

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– Student preparedness. – Student diversity.

– Student career goals and the need for workplace skills (e.g., technology skills, data analysis skills). – Quantitative skills demanded by more disciplines (e.g., the social sciences).

– Advances in technology (e.g., software for teaching, learning, and assessment; massive open online courses (MOOCs); growth in the use of computation as a means for enhancing conceptual understanding).

– State budget cuts for post-secondary education and shifts in states’ priorities from funding based on enrollment to funding based on completion.

In The Mathematical Sciences in 2025, NRC called for mathematics departments to rethink the types of students they attract and to identify the top priorities for educating these students. Change is unquestionably coming to lower-division undergraduate mathematics, and it is incumbent on the mathematical sciences community to ensure it is at the center of these changes, not on the periphery. In their Engage to Excel report, PCAST acknowledged that fewer than 40 percent of students who enter college intending to major in a STEM field actually go on to complete such a degree. They concluded that retaining more STEM majors is the best option for addressing the inadequate supply of STEM professionals in the United States workforce. An additional aspect of the retention challenge is retaining underrepresented groups (minorities and women) in mathematical sciences degree programs at all levels, undergraduate through doctoral.

Our community recognizes that many students encounter significant barriers along the traditional route to a STEM career in their mathematics courses and thus possess inadequate mathematical competencies when they enter the workforce. The Mathematical Sciences in 2025 (NRC, 2012) suggested that we re-assess the training of future generations of mathematical scientists in light of the increasingly cross-disciplinary nature of STEM fields. In its response to the PCAST report, the American Mathematical Society (AMS) affirmed the mathematical community’s commitment to preparing students for success in STEM careers and asserted that it is essential for mathematicians to engage in designing and teaching courses that form the foundation of STEM education. It also referenced many current efforts in undergraduate education designed to address the challenges of teaching entry-level college mathematics. Further, it called for the mathematical sciences commu-nity to develop and share new approaches and teaching methods to enhance the learning experience for STEM majors (Friedlander et al., n.d.). Promising curricular updates and pedagogical practices have since been recommended. However, few such practices are being implemented at a scale nec-essary to substantially increase the number of mathematics graduates entering the workforce, the number of students pursuing a degree in the mathematical sciences, or the number of graduates in all fields who have adequate mathematics skills and competencies to meet current workforce demands. By bringing together thought leaders from various sectors within higher education and beyond, Common Visionwill ultimately serve to catalyze widespread adoption of modernized curricula and pedagogies toward the goal of producing a more mathematically-literate citizenry.

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1.3 The collective enterprise of teaching

Research on “collective impact” (Kania & Kramer, 2011) suggests that, in achieving significant and lasting change in any area, a coordinated effort supported by major players from all existing sectors is more effective than an array of new initiatives and organizations. TheCommon Vision project encourages such action by highlighting existing efforts and draws on the collective wisdom of a diverse group of stakeholders to articulate a shared vision for modernizing the undergraduate mathematics program.

It is thus critical to the success of this project that we have participation from a broad range of professional associations. The Conference Board of the Mathematical Sciences (CBMS) is an umbrella organization consisting of seventeen professional associations, all of which have as one of their primary objectives the increase or diffusion of knowledge in one or more of the mathematical sciences. Five of the seventeen – the American Mathematical Association of Two-Year Colleges (AMATYC), the American Mathematical Society (AMS), the American Statistical Association (ASA), the Mathematical Association of America (MAA), and the Society of Industrial and Applied Mathematics (SIAM) – focus on undergraduate education to some degree. Project leaders have thus been drawn from AMATYC, AMS, ASA, MAA, and SIAM.

AMATYC, founded in 1974, is the only organization exclusively devoted to providing a national forum for the improvement of mathematics instruction in the first two years of college. Central to its mission are promoting and increasing awareness of the role of two-year colleges in mathematics education, and communicating the perspectives of two-year college mathematics educators to public, business, and professional sectors. AMATYC has approximately 1,800 individual members and more than 150 institutional members in the United States and Canada.

AMS was founded in 1888 to further the interests of mathematical research and scholarship. Through its publications, meetings, advocacy, and other programs, the AMS supports mathematics education at all levels and fosters an awareness and appreciation of mathematics and its connec-tions to other disciplines and everyday life. Members include almost 30,000 individuals and 580 institutional members worldwide.

ASAis the world’s largest community of statisticians, the “Big Tent for Statistics.” ASA supports excellence in the development, application, and dissemination of statistical science through meet-ings, publications, membership services, education, accreditation, and advocacy. Founded in 1839, ASA is the second-oldest continuously operating professional association in the country. Since its inception, the association has had a close affiliation with the statistical work of the United States government, particularly the Bureau of the Census. Today, ASA serves 18,000 members worldwide.

MAA is the largest professional association that focuses on mathematics accessible at the un-dergraduate level. Members include university, college, and high school teachers; graduate and undergraduate students; pure and applied mathematicians; computer scientists; statisticians; and many others in academia, government, business, and industry. The mission of MAA is to advance the mathematical sciences, especially at the collegiate level. MAA was established in 1915 and currently serves 17,000 individual and institutional members worldwide.

SIAM, incorporated in 1952, is an international community of over 13,000 individual members. Al-most 500 academic, manufacturing, research and development, service and consulting, government,

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and military organizations worldwide are institutional members. Through publications, research, and community, SIAM pursues its mission to build cooperation between mathematics and the worlds of science and technology. SIAM’s goals are to advance the application of mathematics and computational science to engineering, industry, science, and society; promote research that will lead to effective new mathematical and computational methods and techniques for science, engi-neering, industry, and society; and provide media for the exchange of information and ideas among mathematicians, engineers, and scientists.

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2 Existing Recommendations

Phase I of our two-part initiative centers on introspection. Many publications have guided our thinking, and we have chosen seven curricular guides on which to focus. Each of these seven guides targets undergraduate courses and programs and is endorsed by the supporting association. At a time of rapidly declining membership numbers for many professional associations, it is relevant to reflect on the value of such organizations; we recognize the significant ongoing work of these associations’ members assessing current practices and publishing recommendations for curricula and pedagogy.

• Beyond Crossroads, released in 2006, is AMATYC’s update of the 1995 publicationCrossroads in Mathematics: Standards for Introductory College Mathematics Before Calculus.

http://beyondcrossroads.matyc.org/

• Guidelines for Assessment and Instruction in Statistics Education College Report is ASA’s 2005 publication with recommendations for introductory statistics curricula. ASA’s Guide-lines for Assessment and Instruction in Statistics Education (GAISE) project consisted of two groups focused on K-12 education and introductory college courses, respectively. This publication presented the recommendations developed by the college-focused group.

http://www.amstat.org/education/gaise/

• Curriculum Guidelines for Undergraduate Programs in Statistical Science. These guidelines were endorsed by the ASA board of directors in 2014.

http://www.amstat.org/education/curriculumguidelines.cfm

• The Committee on the Undergraduate Program in Mathematics Curriculum Guide. MAA’s Committee on the Undergraduate Program in Mathematics (CUPM) is charged with making recommendations to guide mathematics departments in designing curricula for their under-graduate students. CUPM began issuing guidelines in 1953, updating them at roughly ten-year intervals. The most recent guide was published 2015.

http://www.maa.org/sites/default/files/pdf/CUPM/pdf/CUPMguide_print.pdf

• Partner Discipline Recommendations for Introductory College Mathematics and the Implica-tions for College Algebra. Curriculum Renewal Across the First Two Years (CRAFTY) is a subcommittee of CUPM and is charged with monitoring ongoing developments in curricula for the first two years of college mathematics and making general recommendations. This guide was completed in 2011.

http://www.maa.org/sites/default/files/pdf/CUPM/crafty/introreport.pdf

• Modeling across the Curriculum. The first SIAM guide provided a summary of the Modeling across the Curriculum workshop held in 2012 and makes recommendations on curricula in areas relevant to applied and computational mathematics. The second such workshop was held in January 2014, and investigated ways to increase mathematical modeling across un-dergraduate curricula and to develop modeling content for the K-12 educational arena.

http://www.siam.org/reports

• Undergraduate Programs in Applied Mathematics was released by SIAM in 2014.

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Additional background on each of these guides is included in Appendix B. A number of other reports published within our community, which are listed in Appendix C, re-affirmed these recommenda-tions and provided additional guidance for this report.

Topics discussed in the following section appear in all seven of the guides. In the subsequent section, we include other issues that appear in at least one of the guides or elsewhere in the literature that we believe warrant significant attention from the mathematical sciences community.

2.1 Common themes

We want to re-iterate the fact that all seven curricular guides declared thatthe status quo is unacceptable. The specific areas that all the guides agreed require significant further action fall into one of four categories: curricula, course structure, workforce preparation, and faculty development. These are, of course, interdependent and do not exist in isolation; we acknowledge that any particular issue might fit in more than one of these categories. We also acknowledge that some of these are not under the exclusive control of faculty members and, thus, change will require the participation of others. Improving teaching and learning requires well-coordinated efforts by multiple stakeholders, including faculty, administrators, employers, professional associations, and funding agencies.

2.1.1 Curricula

While this project focuses on courses taken in the first two years of college, it is impossible to discuss them without an eye toward subsequent courses and the understanding that “an appropriate developmental progression is required to obtain mastery” (ASA, 2014, p. 9). While some of the guides recommended specific courses for the first two years, others do not, and hence we do not list course recommendations here.

All the guides agreed that instructors should present key ideas and concepts from a variety of perspectives, employ a broad range of examples and applications to motivate and illustrate the material, promote awareness of connections to other subjects, and introduce contemporary topics and their applications. Instructors should intentionally plan curricula to:

• Enhance students’ perceptions of the beauty, vitality, and power of the mathematical sciences. • Enhance students’ understanding of mathematics as a creative endeavor.

• Increase students’ quantitative and logical reasoning abilities needed for informed citizenship and for the workplace.

• Increase students’ confidence and joy in doing mathematics and statistics.

• Improve students’ ability to communicate quantitative ideas orally and in writing (and since a precursor to communication is understanding, improve students’ ability to interpret infor-mation, organize material, and reflect on results).

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• Encourage students to continue taking courses in the mathematical sciences.

More pathways. The mathematical sciences community must begin to think in terms of a broader range of entry-level courses and pathways into and through curricula for all students, including mathematics and other STEM majors as well as non-STEM majors. High national unemployment generates additional mathematics majors at higher education institutions (Bressoud, 2010), but we must remain vigilant during times of increased economic prosperity to ensure we continue to attract majors. Our community must remain attentive and design curricula to “address the needs of as many academic paths and disciplines as possible” (AMATYC, 2006, p. 38).

All seven of the guides call for multiple pathways into and through mathematical sciences curricula, some of which should include early exposure to statistics, modeling, and computation. Data-driven science is reshaping the processes of discovery and learning in the 21st century. The current attention to big data and the demand for college graduates with data skills should prompt changes in our entry-level courses which result in students being better prepared for jobs requiring computational and statistical skills. Thus, there is a call to provide mathematically substantive options for students who are not headed to calculus. These entry courses should focus on problem solving, modeling, statistics, and applications. Current college algebra courses serve two distinct student populations: (1) the overwhelming majority for whom it is a terminal course in mathematics, and (2) the relatively small minority for whom it is a gateway to further mathematics. Neither group is well-served by the traditional version of the college algebra course. There is a mismatch between a curriculum designed to prepare students for calculus and the reality that only a small proportion of these students subsequently enroll in calculus (MAA, 2012, p. 49). We acknowledge the need to focus on the calculus sequence and ensure that pathways to it remain a high priority, as calculus is central to most further study in the mathematical sciences, but it behooves us to develop curricula effective for the majority of the population as well.

Mismatched curricula and lack of satisfactory communication between mathematics departments and other academic units are not new. Indeed, according to the MAA (2004):

. . .many view the formal study of mathematics as irrelevant or tangential to the needs of today’s society. They see mathematics departments as disconnected from other dis-ciplines except through a service component that they believe is accepted only reluc-tantly and executed without inspiration or effectiveness. Such views were expressed by a majority of the academic deans at the research universities sampled for the Ameri-can Mathematical Society (AMS) study Towards Excellence: “The prevalent theme in every discussion [with deans] was the insularity of mathematics. Mathematicians do not interact with other departments or with faculty outside mathematics, many deans claimed. The deans. . .seemed to view mathematics departments as excessively inward looking.” This perception is often due more to poor communication than to a lack of effort or good intention. At the least, it points to the need for better communication (p. 3).

On a positive note, this is not the case for those of us who enjoy very good relations with partner discipline departments at our institutions. The AMS study cited by MAA was conducted in the

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1990s, and we hope our more recent personal experiences signal that some progress has been made on this front.

There are existing examples of various pathways into mathematics that include courses with more focus on statistics and modeling. In mathematics departments at four-year institutions, elementary-level statistics enrollments in fall 2010 exceeded the elementary-levels for fall 2005 by about 56 percent, and enrollments have more than doubled since fall 1995 (CBMS, 2103, p. 1). TheCurriculum Guidelines for Undergraduate Programs in Statistical Science(American Statistical Association Undergraduate Guidelines Workgroup (ASAUGW), 2014) suggested there is an opportunity for ASA to lead an effort to re-assess curricula for a variety of introductory statistics courses and that this effort might include creating model courses for students who have completed AP Statistics and those planning to major in statistics (p. 17).

SIAM’s report (2014) of its second Modeling Across the Curriculum workshop questioned whether there are points of entry into the mathematical sciences besides the traditional calculus track:

• Might a freshman mathematics modeling class interest students in applied mathematics who might not otherwise choose mathematics as a major?

• Within the calculus track, is there a new approach that would improve student outcomes? Acknowledging that points of entry and degree paths have changed, Howard Hughes Medical In-stitute (HHMI) President Robert Tijan said, “These days, a large number of students are arriving at college through remarkably diverse pathways. The scientific leader of tomorrow may be in a community college today or she may be a first-generation college student. Higher education should acknowledge these differences among students and create programs that offer diverse entry points and pathways to STEM degrees” (HHMI, 2015). Indeed, HHMI has recently strengthened their commitment to STEM education by offering $60 million in science education grants intended to challenge colleges and universities to increase their capacity to engage all students in science. In a significant departure from past initiatives, this competition is open to more than 1500 institutions in the United States that offer bachelor’s degrees in the natural sciences, including liberal arts colleges, master’s-granting universities, and research universities. Previous HHMI science education grant competitions were by invitation only and restricted to approximately 200 designated undergraduate institutions.

Statistics. The CRAFTY guide (2011) noted the importance of data analysis for many of our partner disciplines and argued strongly for an increased presence of basic statistical training in the first two years of undergraduate mathematics. According to ASAUGW (2014), “To be prepared for statistics and data science careers, students need facility with professional statistical analysis software, the ability to access and manipulate data in various ways, and the ability to perform algorithmic problem-solving” (p. 4). The material should be motivated by a variety of examples and real data sets, including data collected by students. Entry-level courses should reflect the discipline and prepare students to take additional courses.

One of the content standards inBeyond Crossroads(AMATYC, 2006) recommended requiring stu-dents to collect, organize, analyze, interpret, and use data to make informed decisions. MAA (2015) recommended that students in the mathematical sciences work with professional-level technology tools (e.g., statistical packages) and acquire modest programming skills that can help them tackle

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ill-posed, real-world problems (p. 11). Such skills will prepare them for workplace demands since “using technology to address challenges has become a defining characteristic of work in the 21st century” (Change the Equation, 2015, p. 2). While an increased presence of statistics in the cur-riculum is valuable in its own right, it is also the case that exposing students to statistical modeling and simulation in their mathematics courses will enhance their computational skills (ASA, 2014, p. 7).

Modeling and computation. Modeling and computation can be used to introduce the scientific method and experimentation into mathematics courses, and both should also be seen as a means for enhancing conceptual understanding.

According to SIAM (2012), “Models are a simplification of reality, and can come in many forms. Some models are physical devices, such as a scaled-down model airplane. Other models are expressly quantitative in that they are phrased in the symbolic language of mathematics. We refer to these as mathematical models, and they can take the form of equations, algorithms, graphical relations, and sometimes even paragraphs” (p. 11). Here, we use the term “modeling” as an umbrella term referring to the creative process that can be mathematical, statistical, computational, data-based, or science-based.

The same SIAM guide recommended that departments offer modeling experiences at the entry level by developing “a first year modeling/applied mathematics course that precedes and motivates the study of calculus and other fundamental mathematics for STEM majors” (p. 4). A central reason for introducing students to modeling is to engage and retain students in STEM disciplines. Indeed, applications of fundamental mathematics, computation, statistics, and science in a wide range of STEM fields can be particularly appealing to potential majors.

Virtual experimentation is replacing many aspects of real-world implementation, and the demand for modelers is rapidly increasing. For example, in the context of airplane design or pharmaceutical testing, real-world experimentation is too dangerous, and models can be used to preserve human capital and other resources. In the context of financial markets, the complexity of the models and implied ability to run very large virtual experiments makes the use of models even more appealing. These kinds of shifts are increasing the workforce demand for graduates with modeling skills. “There are substantial opportunities for the mathematical community to attract and retain students if we can adapt to this growing opportunity” (SIAM, 2014, p. 29).

Designing curricula that integrates modeling, data science, information science, and computational science is challenging. At the second SIAM Modeling Across the Curriculum workshop, participants asserted that our community needs a common language and should eliminate jargon and academic silos. They posited that physically housing fields together, e.g., as an applied and computational mathematics department, might benefit students directly by exposing them to ways in which the fields interact. Because some introductory material is the same across fields, a single department might also realize efficiencies in staffing entry-level courses.

Some of the guides specifically called for development of stronger computational skills in math-ematics and other STEM majors. The recommendations range from first year students learning simple tasks like managing electronic files and handling different types of file formats to mathemat-ical science majors taking an introductory programming course. Some of these can be addressed in mathematics courses; one example is requiring students in mathematics courses to use software

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packages (e.g., MATLAB) that are standard in engineering practice.

Undergraduate statistics majors in particular should develop skills that enable them to handle in-creasingly complex data and use sophisticated data analysis approaches. Graduates should be facile with professional statistical software and other tools for data exploration, cleaning, and validation. They should possess the ability to program in a higher-level language (including the ability to write functions and use control flow in a variety of languages and tools such as Python, R, SAS, or Stata), to think algorithmically, to use simulation-based statistical techniques, and to conduct simulation studies. They should also be proficient with managing and manipulating data, including joining data sets from different sources in different formats and restructuring data into a form suitable for analysis. Acquisition of these skills should begin during their first two years of college.

Considerable faculty creativity may be required to fully integrate additional data-related, statistical practice, and computational skills into the curriculum, making relationships with faculty in the computational sciences and partner disciplines that teach applied statistics even more important. For faculty inexperienced in teaching these skills, professional development in this area is critical and should be considered a priority.

Connections to other disciplines. Faculty in other disciplines particularly value introductory mathematics courses that focus on skills used in their disciplines. All guides recommended employ-ing a broad range of classic and contemporary applications that promote awareness of connections to other subjects, strengthen each student’s ability to apply the course material in other contexts, and enhance student perceptions of the relevance of mathematics to the modern world.

Throughout the guides, we see the call for increased attention to the needs of other disciplines. For example, CRAFTY described chemistry students’ need for early introduction of multidimensional topics. This guide criticized calculus and linear algebra courses taught with a strong theoretical focus that students view as obscure, formidable, and irrelevant to other disciplines. This is par-ticularly problematic given that these two specific courses are foundational to many majors in the mathematical sciences and topics taught in these courses are necessary for many applications. For example, singular-value decomposition in linear algebra is a widely used technique in statistics, computer science, engineering, finance, and economics. Mathematicians are familiar with the topic, but many are unfamiliar with numerical algorithms developed the 1960s and 1970s due to the delay of their appearance in texts. Example topics appropriate for introduction in calculus range from a first look at Fourier series (the basis for signal processing algorithms) to Monte Carlo methods (a first step toward understanding Markov Chain Monte Carlo methods).

Mathematicians should seek (1) applications from partner disciplines for use in mathematics courses, (2) team teaching opportunities with faculty in partner disciplines, and (3) input from business and industry on desired workplace skills. They should collaborate with partner disciplines to explicitly translate notation and terminology among the disciplines in order to enhance students’ ability to see connections across disciplines.

Communication. Students must learn to communicate complex ideas in ways that are under-standable to collaborators, clients, employers and other audiences. Critical communication skills include the ability to produce accessible visualizations of material, effective technical writing, and strong presentation skills.

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The relative importance of each communication skill depends somewhat on the field of study. For example, a theoretical mathematics student should be able to state problems clearly, understand mathematical readings, and communicate mathematical ideas both orally and in writing to audi-ences with disparate levels of mathematical sophistication. For statistics students, effective techni-cal writing skills are of utmost importance. These types of skills develop over time and, therefore, opportunities to hone them should begin in the first two years of study.

Transitions. The first two years of college mathematics and statistics should be viewed compre-hensively within the context of the transition from secondary to post-secondary education and the transition from two-year to four-year institutions. Our community must (1) articulate clear path-ways between curricula driven by changes at the K-12 level and the first courses students take in college, (2) ensure students are correctly placed in entry-level courses, and (3) find ways to remove barriers facing students who attempt to transfer from one institution to another.

Appropriate placement in entry-level courses is an ongoing challenge in higher education. Despite the tremendous amount of effort and resources devoted to establishing effective placement mecha-nisms, many agree that our community has not solved the problem of placing students in appropriate entry-level courses. In addition, traditional placement efforts have focused primarily on accurate placement in mathematics and not in statistics because students entering college rarely had any background in that subject; this is no longer the case. In 2014, more than 184,000 students took the Advanced Placement (AP) statistics exam, a nine percent increase over the 2013 participation rate (The College Board, 2014). To put this in perspective, about 213,000 took the AP Calculus AB exam in 2014. In fact, the first administration of the AP exam in statistics drew more than any other AP exam had at that point. There has been a corresponding increase in the number of bachelor’s degrees granted in statistics, a total increase of more than 140 percent since 2003 with a 21 percent increase between 2012 and 2013 (ASA, 2014, p. 4). The dramatic growth in the number of high school students completing an AP statistics course has caused some institutions to re-evaluate their introductory courses in statistics and data science. All institutions should develop courses appropriate for students who have taken AP statistics in high school, distinct from courses for those who have no previous exposure to statistics. These developments underscore the challenge of placing students in statistics courses that align with their backgrounds.

Two-year colleges are a large, growing, and increasingly important component of the United States higher education system; in fact, these institutions enroll nearly half of all undergraduates in this country (Bellafante, 2014). Indeed, President Obama recently announced an initiative to mint five million more community college graduates by 2020, a remarkable goal given that just over 77,000 associate degrees and certificates were awarded in 2011-2012 by community colleges (American Association of Community Colleges, 2015). According to Two-Year Contributions to Four-Year Degrees (National Student Clearinghouse Research Center, 2015), 46 percent of all students who completed a degree at a four-year institution in 2013-2014 had been enrolled at a two-year institution at some point in the previous 10 years. But many challenges surround the process of student transfer, including inadequate financial aid, the need for students to work excessive hours while attempting to carry a full load of courses, insufficient transfer advising, and the fact that too few course credits transfer from two-year to four-year institutions (The National Center for Public Policy and Higher Education, 2011). The Curriculum Guidelines for Undergraduate Programs in Statistical Science (ASAUGW, 2014) asserted that “[a]dditional efforts are needed to coordinate statistics instruction at the two-year college level, raise the profile of statistics majors at these

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institutions, and facilitate articulation agreements for transfer to four-year institutions” (p. 17). Several states, including Arizona, California, and Texas, where many students are from traditionally underserved groups or the first in their family to attend college, will experience rapid growth in the number of high school graduates in the next decade. These states rely heavily on two-year colleges as the point of entry to post-secondary education, but their current rates of transfer are unacceptable. Failure to improve these rates, as well as their bachelor’s degree completion rates, will mean that many students in these states will be unable to reach their educational goals. Consequently, the nation as a whole will face an even larger shortage of bachelor’s degree holders than currently exists (The National Center for Public Policy and Higher Education, 2011).

Two-year college students who do manage to transfer to four-year institutions succeed at a slightly higher rate than students who went to a four-year institution straight out of high school, but the problem is that too few of them find the means to overcome all the obstacles standing in their way. Our community must find ways to remove these obstacles. CUPM’s 2015 guide pointed to an effective program, The Illinois Articulation Initiative, which requires that changes in general education and transfer courses be coordinated jointly by the Illinois Mathematical Association of Community Colleges (IMACC) and the Illinois Section of the Mathematical Association of America (ISMAA). Additional strategies for paving the way for transitions from two- to four-year institutions are outlined in a recent Jack Kent Cooke Foundation report (Giancola & Davidson, 2015).

2.1.2 Course structure

Pedagogy. Across the guides we see a general call to move away from the use of traditional lecture as the sole instructional delivery method in undergraduate mathematics courses. The ASA (2005) asserted that, “[a]s a rule, teachers of statistics should rely much less on lecturing and much more on alternatives such as projects, lab exercises, group problem-solving, and discussion activities” (p. 9). Even within the traditional lecture setting, we should seek to more actively engage students than we have in the past.

All seven guides stressed the importance of moving toward environments that incorporate multiple pedagogical approaches throughout a program. Oft-cited examples are active learning models where students engage in activities such as reading, writing, discussion, or problem solving that promote analysis, synthesis, and evaluation of class content. Cooperative learning, problem-based learning, and the use of case studies and simulations are also approaches that actively engage students in the learning process (University of Michigan Center for Research on Learning and Teaching, n.d.). These types of pedagogies promote collaboration and provide opportunities to practice communicating ideas. A multifaceted approach to instruction is important for helping students develop flexibility in the ways they process information, and the use of diverse instructional approaches should be a strategic part of the curriculum.

A common misconception is that information is easier to process when it matches a person’s pre-ferred cognitive style (Pashler, et al, 2008). This theory, known as the “matching hypothesis” in education, suggests that “visual learners” and “auditory learners” engage best with material presented in their preferred mode. Yet, research suggests that style flexibility may actually be more important. Teaching a student to select the most appropriate style for a given situation

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among a variety of styles and to switch styles when necessary is a much more beneficial approach. (Kozhevnikov, 2014).

Technology.All seven guides advocated using technology to enhance student learning. Pedagogical innovations are often driven by advancing technologies. Faculty and students should learn to use technology and become intelligent consumers of the answers it provides. Technology can be used as a tool for developing conceptual understanding, analyzing data, and for solving problems. It can strengthen students’ problem-solving skills by encouraging them to employ multiple strategies (graphical, numerical, algebraic) in the process. Students can use technology to perform extensive computations (e.g., with large data sets in statistics or on large systems in linear algebra) that are unrealistic by hand and to generate visualizations such as graphs, histograms, and other diagrams that enhance comprehension.

[T]echnology can promote students’ exploration of and experimentation with mathe-matical ideas. For example, students can be encouraged to ask “what if?” questions, to posit conjectures, to verify or refute them, and to use technology to investigate, revise, and refine their predictions. Specific examples include studying the effects of manipu-lating parameters on classes of functions and fitting functional models to data (MAA, 2004, p. 24).

Using specialist software (e.g., R or MATLAB) for teaching can also provide students direct expe-rience with tools routinely used in the workplace. Indeed, Beyond Crossroads (AMAYTC, 2006) recommended using technology throughout the curricula to help students discover properties, de-velop concepts, consider multiple perspectives, and to give students experience with the technology skills they will use routinely in the workplace.

2.1.3 Workforce preparation

Mathematical sciences departments play a major role preparing a mathematically- and scientifically-literate workforce. While we acknowledge there is no one-size-fits-all solution, we also recognize the need for structures to catalyze widespread adoption of curricula and evidence-based pedagogies that are (1) geared toward developing a broad base of intellectual skills and competencies to better prepare students for the workforce and (2) endorsed by the mathematical sciences community. In response to rapidly changing workforce needs, departments should establish advisory commit-tees that include representatives from business, industry, and government to regularly engage in conversations about the expectations of prospective employers. Departments must engage partners from inside and outside academia in STEM and non-STEM fields to ensure that the applications taught are realistic and that the skills students take from courses are valued by stakeholders. Our community must prepare graduates who are career-ready and focus intentionally on workplace skills early in their programs. Even in the first two years of college, students must have opportunities to improve their speaking and writing skills, to work with data, and to engage in open-ended inquiry. Data skills, in particular, are increasingly attractive to employers. According toFueling Innovation and Discovery(NRC, 2012):

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The mathematical sciences contribute to modern life whenever data must be analyzed or when computational modeling and simulation is used to enable design and analysis of systems or exploration of “what-if” scenarios. The emergence of truly massive data sets across most fields of science and engineering, and in business, government, and national security, increases the need for new tools from the mathematical sciences (p. 2).

STEM and non-STEM graduates with marketable skills contribute to the “common good” by advancing national priorities that are in the best interests of all citizens. Mathematical competencies lead to higher-paying careers and, thus, can play a profound role in students’ economic mobility (Haskins, Holzer, & Lerman, 2009).

In its conclusion,Beyond Crossroads(AMAYTC, 2006) highlighted the critical importance of part-nerships with other disciplines as well as with business and industry employers. It asserts:

Technical mathematics courses and programs should be developed in collaboration with faculty from other disciplines and business and industry representatives to identify and address the mathematics content needs of specific program employers. Content in two-year technical mathematics courses should be selected because of its application to a specific technical field and the needs of specific employers. It should also be at a level equivalent to mathematics courses that transfer to four-year institutions (p. 44).

Partnerships inside the institution. Faculty in disciplines outside mathematics rarely ask their students to find the equation of the line that passes through two given points. But social scientists, for example, will expect students to recognize a linear pattern in a set of data, interpret the parameters of the line of best fit, and use the equation of the line to answer questions in the context of a real-world scenario. Mathematical sciences departments should be aware of applications used in other disciplines and adjust their general education and introductory courses accordingly (MAA, 2004).

In discussing the role of modeling in the curriculum, SIAM (2102) distinguished between math-ematical models and mathmath-ematical modeling. The former refers to the presentation of finalized models that primarily expose students to applications of abstract mathematics (e.g., exponential functions to mimic population growth) without attention to derivation or assumptions behind the models. The latter attends to “the creative process by which the model is developed” (p. 11), including construction and evaluation criteria. Both instructional approaches are strengthened when mathematics faculty members draw on partnerships with faculty in other disciplines. SIAM asserted:

By working across campus, faculty can develop strong ties. If done well, modeling will help bind applied mathematics to the rest of STEM. We recommend constant outreach, continually making new connections. An additional advantage of community building is that it allows for better leveraging of existing infrastructure and resources. Intellectual diversification will also make mathematics a central theme and not allow the modeling to become dominated by a specific scientific discipline (p. 13).

Partnerships outside the institution. Departments should periodically consult with represen-tatives from local businesses and industries and use this input to ensure course content remains

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relevant.

Each department should be well-informed about the paths their graduates choose and should use that information to inform decisions about their courses and programs. AMATYC called on two-year institutions to implement methods for tracking their students after they graduate or transfer and consider whether or not their mathematics courses and programs appropriately address stu-dents’ educational and career needs. Echoing this, ASA (2014) suggested departments survey both graduates and employers to gather information on the career paths of the growing number of statis-ticians in the workforce and use this information to guide curricular decisions.

An important aspect of workforce training is ensuring students, parents, guidance counselors, teach-ers, and administrators are aware of the vast array of career options available to mathematics and statistics graduates. Students should be well-informed of the possibilities before they choose a col-lege major. Faculty members teaching courses in the first two years of colcol-lege should also understand which skills are needed for various career paths.

A math degree can prepare students for high-paying and influential careers in finance, insurance, risk management, operations research, computational science and engineer-ing, signal, image, and natural language processengineer-ing, bioinformatics and computational biology, information science, and machine learning, to name a few (SIAM, 2012, p. 13). Other career fields that could be added to this list are advanced manufacturing, national security, STEM education, and data science as used, for example, in climate science, international develop-ment, and health care.

2.1.4 Faculty development and support

Higher education as an industry invests little in the development of its front-line instructional staff, but ongoing training and support are necessary in all mathematical fields, perhaps especially in emerging areas in the mathematical sciences. Given the limited number of programs run by pro-fessional associations that have been instrumental in developing mathematics faculty (e.g., MAA’s Project NExT and AMATYC’s Project ACCCESS), it is no surprise that the need for developing both full-time and contingent faculty is highlighted in all the guides. In order to adapt curricula, develop new courses, incorporate pedagogical tools, and use technology effectively for instruction, faculty members require training, resources, and rewards for their efforts.

ASA’sCurriculum Guidelines for Undergraduate Programs in Statistical Science(ASAUGW, 2014) articulated the need this way:

A considerable barrier to implementing these guidelines is the lack of materials related to data science topics. Efforts to pull together activities, projects, sample syllabi, and model courses as well as training are needed to ensure that faculty have the appropriate skills to teach aspects of this new curriculum (p. 11).

As AMS pointed out in its response (www.ams.org/policy/govnews/pcast-statement) to the PCAST report (2012), it is essential that mathematicians become engaged in planning and teaching

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courses that form the foundation of STEM education. Notably, this will require training for faculty in priority areas emphasized by ASA that have attracted attention from stakeholders outside the academy, including from the federal government with their recent focus on big data (Kalil, 2012). Faculty training in these areas merits substantial investment as does training for all faculty in the mathematical sciences. In a recent white paper, ASA (2014) pointed to

. . . scientific challenges facing many broad areas being transformed by Big Data – in-cluding healthcare, social sciences, civic infrastructure, and the physical sciences – and describes how statistical advances made in collaboration with other scientists can ad-dress these challenges. We recommend more ambitious efforts to incentivize researchers of various disciplines to work together on national research priorities in order to achieve better science more quickly (p. 1).

AMATYC (2006) highlighted the need to “provide support for faculty in seeking outside funding to support the technology appropriate for the curriculum” (p. 45). And SIAM (2012) urged administrators and other funders to “provide seed grants for faculty to develop, implement and evaluate new approaches to the high school-college math transition for STEM majors” (p. 4). It is critical that faculty engage with efforts to improve teaching and strengthen curricula, including curricula in the first two years for both majors and non-majors. Faculty members and departments are less likely to respond to this call if they are not rewarded for their efforts, and they will be unable to respond in a meaningful way if institutions fail to provide ongoing professional development and support. Administrators who understand the critical role that the mathematical sciences play in economic mobility are more likely to invest in faculty development, and it is up to mathematicians and statisticians to communicate this vital role.

Departments and institutions must also engage in an ongoing cycle of self-reflection and revision. The MAA (2015) called on departments to continually strengthen courses and programs to better align with student needs and to assess the effectiveness of such efforts. Curricula and programs require updates if they are to maintain relevance to current job opportunities for professional mathematicians, statisticians, and other graduates who possess strong STEM skills. Mathematical sciences departments and institutional administrators should support and reward faculty efforts to improve teaching and to strengthen curricula.

SIAM (2012) emphasized that modernizing undergraduate curricula cannot be delegated to a few pioneers:

Sustainability is a big challenge. Many past efforts and programs have not survived on account of the founders leaving, retiring, or burning out. Therefore, we recommend getting many people involved so that efforts are integrated into the culture and become a community effort, not something being driven by one or two people (p. 13).

They went on to say that the greater the number of faculty members involved and the greater the investment in infrastructure, the more likely the program is to survive in the long run. MAA (2004) also addressed the issue of sustainability:

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long-term sustainability, initiatives must be team efforts, with faculty in supporting roles who can be prepared to expand or take over the leadership of the program. At insti-tutions that require research for promotion and tenure, untenured faculty should not be expected to take on roles that would seriously hamper their scholarly development. However, means should be found to involve all faculty in improving the curriculum and its instruction. This is especially true for younger faculty who often bring enthusiasm and openness to innovative ideas (p. 25).

The mathematical sciences community must foster an institutional culture that adequately encour-ages and values work on the problems highlighted in this report without over-stretching the goodwill and enthusiasm of faculty members. Large-scale changes are needed and the Coalition for Reform of Undergraduate STEM Education (Fry, 2014) recommended convening “national summits focused on the development of new systems and approaches for faculty incentives, including promotion and tenure, and faculty development programs that are organized to achieve optimal impact on strengthening teaching and learning” (p. 7). The MAA (2015) asserted:

Failing to align rewards with department needs for renewal and reform leads to stag-nation. A department that values faculty involvement in undergraduate research, in-terdisciplinary courses, experimental coursework, and new pedagogy should assure that suitable credit is awarded in annual reviews. Deans, department chairs, and colleagues should recognize that colleagues who risk doing innovative work deserve both encour-agement and support in the planning and execution stages of projects and appropriate rewards when they come up for periodic review (p. 57).

2.2 Other important themes

In addition to the four themes identified above as common to all guides, there are a number of other areas that warrant considerable attention from the mathematical sciences community, but that do not appear in all the guides. We view increased attention to these as critical for improving undergraduate mathematical sciences education and want to highlight them as additional areas of focus. Indeed, they are compelling and, together with the common themes in Section 2.1, form the basis of our recommendations for moving forward that are outlined in Chapter 3. As with the common themes, the topics here are interdependent.

Student diversity. The fact that our community has been unable to attract and retain a diverse student population in the mathematical sciences is a dreadful shortcoming that must be remedied. The underrepresentation of minorities in advanced mathematics courses is an ongoing problem. Walker (2007) noted that, while there has been some improvement since Stiff and Harvey (1988) called the mathematics classroom one of the most segregated places in the United States, upper-level mathematics classes remain predominantly white. Black and Latino students are less likely than Asian American and white students to complete advanced high school mathematics courses (National Center for Education Statistics, 2014) and the performance gap in mathematics is evident as early as fourth grade (Fry, 2014, p. 3).

A Common Vision for Undergraduate Mathematical Sciences Programs in 2025 FINAL DRAFT. Karen Saxe Linda Braddy